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The purpose of this paper is to introduce the zero‐modified distributions in the calculation of operational value‐at‐risk.

This kind of distributions is preferred when excess of zeroes is observed. In operational risk, this phenomenon may be due to the scarcity of data, the existence of extreme values and/or the threshold from which banks start to collect losses. In this article, the paper focuses on the analysis of damage to physical assets.

The results show that basic Poisson distribution underestimates the dispersion, and then leads to the underestimation of the capital charge. However, zero‐modified Poisson distributions perform well the frequency. In addition, basic negative binomial and its related zero‐modified distributions, in their turn, offer a good prediction of count events. To choose the distribution that suits better the frequency, the paper uses the Vuong's test. Its results indicate that zero‐modified Poisson distributions, basic negative binomial and its related zero‐modified distributions are equivalent. This conclusion is confirmed by the capital charge calculated since the differences between the six aggregations are not significant except that of basic Poisson distribution.

Recently, the zero‐modified formulations are widely used in many fields because of the low frequency of the events. This article aims to describe the frequency of operational risk using zero‐modified distributions.

The purpose of this paper is to determine single sampling plans (SSPs) by attributes when the number of nonconformities is distributed according to a zero-inflated Poisson (ZIP) distribution.

Manufacturing processes have now-a-days been aligned properly and are monitored well, so that the occurrence of nonconformities would be a rare phenomenon. The information related to number of nonconformities per product will have more number of zeros. Under such circumstances, the appropriate probability distribution of the number of nonconformities is a ZIP distribution. The operating characteristic function of the sampling plan is derived.

Parameters of the sampling plans are obtained for some sets of values of (p ₁, α, p ₂, β). Numerical examples are given to illustrate the selection of SSPs under ZIP distribution and to study its advantages over Poisson SSP.

Results obtained in this paper are original and has been done for the first time in this regard. Parameters of the sampling plans are essential to make decisions either to accept or reject the lots based on the inspection of the samples.

Under a discontinuous and nonlinear compensation scheme, which is prevalent among car dealerships, the amount of a salesperson’s expected daily commission depends primarily on his position in the pay schedule on the day he makes a sale. Salespeople thus vary their efforts and adopt a different pricing strategy week by week, or even day by day. The purpose of this paper is to examine the incentive effect of such a nonlinear scheme and provide the evidence that salespeople’s behavior is consistent with the theory.

The authors conduct regression analyses using the transaction data provided by two North American auto dealerships. The authors construct a daily measure of varying incentive intensity and evaluate its impact on the distribution of individual daily sales and the dealership’s gross profit rate.

The authors find that the daily measure of varying incentive intensity has a positive effect on the distribution of individual daily sales and a negative impact on the dealership’s gross profit rate. The results suggest that: salespeople adjust their effort levels in response to the intensity of incentives; and they game the system by lowering the prices when the marginal return to doing so is high.

The study shows that there is a high cost associated with the discontinuous nonlinear pay scheme, raising the question of why many auto dealerships use it.

This paper sheds light on the undesirable aspects of discontinuous and nonlinear incentive schemes, varied performance and gaming, by quantifying the effects of the worker’s behavior.

The purpose of this paper is to analyze demand forecast strategies to support a more sustainable management in a pallet supply chain, and thus avoid environmental impacts, such as reducing the consumption of forest resources.

Since the producer presents several uncertainties regarding its demand logs, a methodology that embed zero-inflated intelligence is proposed combining fuzzy time series with clustering techniques, in order to deal with an excessive count of zeros.

A comparison with other models from literature is performed. As a result, the strategy that considered at the same time the excess of zeros and low demands provided the best performance, and thus it can be considered a promising approach, particularly for sustainable supply chains where resources consumption is significant and exist a huge variation in demand over time.

The findings of the study contribute to the knowledge of the managers and policymakers in achieving sustainable supply chain management. The results provide the important concepts regarding the sustainability of supply chain using fuzzy time series and clustering techniques.

The objective of this paper is to propose a methodology based on random demand inventory models and dependence structures for a set of raw materials, referred to as “components”, used by food services that produce food rations referred to as “menus”.

The contribution margins of food services that produce menus are optimised using random dependent demand inventory models. The statistical dependence between the demand for components and/or menus is incorporated into the model through the multivariate Gaussian (or normal) distribution. The contribution margins are optimised by using probabilistic inventory models for each component and stochastic programming with a differential evolution algorithm.

When compared to the non-optimised system previously used by the company, the (average) expected contribution margin increases by 18.32 per cent when using a continuous review inventory model for groceries and uniperiodic models for perishable components (optimised system).

The multivariate modeling can be improved by using (a) other non-Gaussian (marginal) univariate probability distributions, by means of the copula method that considers more complex statistical dependence structures; (b) time-dependence, through autoregressive time-series structures and moving average; (c) random modelling of lead-time; and (d) demands for components with values equal to zero using zero-inflated or adjusted probability distribution.

Professional management of the supply chain allows the users to register data concerning component identification, demand, and stock levels to subsequently be used with the proposed methodology, which must be implemented computationally.

The proposed multivariate methodology allows it to describe demand dependence structures through inventory models applicable to components used to produce menus in food services.

Este trabajo propone una metodología basada en modelos de inventarios con demanda aleatoria y estructura de dependencia para un conjunto de materias primas, denominadas “componentes”, usadas por servicios de alimentación que producen raciones alimenticias denominadas “menús”.

Los margen de contribución de servicios de alimentación que producen menús son optimizados empleando modelos de inventarios con demandas aleatorias dependientes. La dependencia estadística entre demandas de componentes y/o menús es incorporada en el modelado mediante la distribución gaussiana (o normal) multivariada. La optimización de los márgenes de contribución se logra usando modelos de inventarios probabilísticos para cada componente y programación estocástica mediante el algoritmo de evolución diferencial.

El margen de contribución esperado (promedio) aumenta en un 18,32% usando modelos de inventario de revisión continua para abarrotes y modelos uniperiódicos para componentes perecederos (sistema optimizado), en relación al sistema no optimizado usado anteriormente por la compañía.

La metodología multivariada propuesta permite describir estructuras de dependencia de la demanda mediante modelos de inventario aplicables a componentes usados para producir menús en servicios de alimentación.

Una administración profesional de la gestión de la cadena de suministros permite registrar datos de la identificación del componente, su demanda y sus niveles de stock para ser usados posteriormente con la metodología propuesta, la que debe estar implementada computacionalmente.

El modelado multivariado puede ser mejorado (a) utilizando distribuciones probabilísticas univariadas (marginales) distintas a la gaussiana, mediante métodos de cópulas que recojan estructuras de dependencia estadística más complejas; (b) considerando demandas de componentes con valores iguales a cero, mediante distribuciones probabilísticas infladas en cero; (c) usando dependencia temporal, mediante estructuras de series de tiempo autorregresivas y de media móvil, y (d) modelando el lead-time en forma aleatoria.

The purpose of this paper is to indicate trade characteristics of Foreign direct investment (FDI) inflows in China and examine the dynamic interaction between FDI inflows and China’s international trade through empirical analysis.

At first, this paper builds the probability distribution model (Poisson and negative binomial (NB)) to capture the characteristics of spatial distribution of all kinds of FDI firms in Chinese cities and provinces based on count data, so as to indicate the potentials for further introducing FDI inflows in China; Second, this paper investigates the effects of trade on FDI firms inflows based on probability regress model (Binary Logit, Tobit, NB, Poisson, zero inflated negative binomial) and shows how international trade accelerates the different kinds of FDI firms to agglomerate in Eastern, Middle and Western region by the endowments of factors; third, this paper empirically examines the magnitude and characteristics of trade effects generated by FDI inflows by building dynamic panel model based on continuous data.

First, statistical tests of probability distribution model based on count data show that there are characteristics of spatial agglomeration of FDI firms such as manufacture firm, R & D firm, managing and marketing firm and total sectors, which obey NB distribution as whole; Second, this study indicate that FDI inflows have strong positive effects on the international trade in China’s provinces and on China’s regional trade, and that most of foreign firms in China are export oriented being strongly characterized as labor-intensive industries, especially, contributions of FDI to imports are greater than the contributions of FDI to exports in China’s Middle and Western trade, and the growth of FDI trade in China’s trade volume has been strong over the past years; third, the empirical results of models based on count data and continuous data indicate that FDI inflows have significantly positive relationship with international trade, that is, the relationship between FDI and international trade in the case of China is the characteristics with complement and imports substituting relationship.

Because of mixed data set for FDI inflows of processing and assembling trade and production-oriented FDI, efficiency-seeking and knowledge or technology – intensive FDI inflows in the past 36 years, the paper only investigate characteristics of FDI inflows in China before the turning point of financial crisis, but it is important for capturing the whole picture of trade characteristics of FDI inflows in China.

The derived quantitative results imply that there are still greater potentials for further introducing FDI inflows in China, and decision-maker should make policy of introducing FDI inflows which are favorable to supporting innovative activities and economic agglomeration, and preferably encourage efficiency-seeking and export-oriented FDI inflows so as enhance quality and efficiency of economic growth, which are also helpful to accelerate upgrade of Chinese industry and gradually shorten gap of growth among Eastern, Middle and Western region.

FDI inflows in China not only stimulate the remarkable growth of bilateral trade between host country and home country, but also promote the growth of international trade between China and the rest of the world. Thus, policies of bilateral or multilateral free-trade and investment area should be encouraged, which will be also favorable to promote the growth and welfare in all the regions.

This paper demonstrates that spatial distributions of FDI firms in Chinese cities and provinces obey NB probability distribution pattern, and puts forward the methodology of model based on count data and continuous data. Besides, this paper quantitatively indicates trade characteristics of FDI inflows in China as well as the dynamic interaction between FDI inflows and China’s international trade.

The purpose of this paper is to provide a better understanding of what drives firms’ choice between exploration alliances and exploitation alliances by examining the role of organizational slack and its interaction with market uncertainty.

An empirical study is conducted based on 1,614 alliances formed by 581 US biotechnology firms, and the hypotheses are tested using a zero-inflated multilevel Poisson model.

The results indicate that firms’ strategic choice to pursue exploration or exploitation alliances is a reflection of organizational intention and adaptation to environmental turbulence. More specifically, firms with more financial slack tend to form more exploration alliances and fewer exploitation alliances. However, under high market uncertainty, firms with financial slack tend to establish more exploitative partnerships and avoid exploration collaborations.

This paper contributes to the literature on exploration–exploitation alliances, which tends to fall short of providing an understanding of why organizations pursue such alliances. By identifying the impact of organizational slack and its interaction with market uncertainty, this study shows that organizations are able to respond to environmental change, and those with capabilities are likely to craft their strategic choice configurations based on their own characteristics.

In the context of increasing consolidation in the banking industry, this research examined one of the motives for bank acquisitions and the kinds of acquisitions made by banking firms. The effect of ownership concentration was tested on the absolute level of bank acquisitions and the average degree of geographic‐market overlap of these acquisitions. In a sample of 156 banking firms, banks featuring dispersed ownership were found to acquire other banks with less market‐overlap than did banking firms with concentrated ownership. However, ownership concentration was not a significant predictor of the absolute level of merger activity. Implications of these differences in acquisition strategies are explored.

The purpose of this paper is to evaluate investor behaviour related to the timing of selling financial assets based on an intuitive evaluation of the current market trend and growth expectation.

The experiment involved 1,052 volunteer participants who made decisions about stock sales in an environment that simulated a home broker platform to negotiate stocks. Zero-inflated regression models were used.

The results show that investors’ attitudes, or beliefs, determine whether they will buy or keep risky assets in their investment portfolios; they may decide to sell such assets, even though market shows an upward trend. Such results make a new contribution to behavioural finance within the context of prospect theory and the disposition effect.

The originality of this paper lies in the use of new and innovative techniques (zero-inflated Poisson and negative binomial regression models) applied to real data obtained experimentally.

Este artigo estuda o comportamento de investidores relacionado ao momento da venda de ativos financeiros com base em uma avaliação intuitiva da tendência atual do mercado e da expectativa de crescimento.

Nosso experimento envolveu 1,052 participantes voluntários que tomaram decisões sobre a venda de ações em um ambiente que simulava uma plataforma de corretagem para negociação. Foram utilizados modelos de regressão inflacionados de zeros.

Os resultados mostram que as atitudes ou crenças dos investidores determinam se eles comprarão ou manterão ativos de risco em suas carteiras de investimento; eles podem decidir vender esses ativos, mesmo que o mercado mostre uma tendência ascendente. Tais resultados constituem uma nova contribuição para o campo das finanças comportamentais, dentro do contexto da teoria do prospecto e do efeito disposição.

A originalidade deste artigo reside no uso de técnicas novas e inovadoras (modelos de regressão Poisson e binomial negativo inflacionados de zeros) aplicadas a dados reais obtidos experimentalmente.

Branching is not the only way for foreign banks to enter a national market, and it is impractical when there are informational and cultural barriers and asymmetries among countries. The purpose of this paper is to analyze the determinants of cross-border branching in the Latin American banking sector, a region with regulatory disparity and political and economic instability, offering elements to a grounded strategic decision.

This study uses data from six Latin American countries. To account for the preponderance of zero counts, classes of zero-inflated models are applied (Poisson, negative binomial, and mixed). Model fit indicators obtained from differences between observed and estimated counts are used for comparisons, considering branches in each region established by banks from every other foreign region of the sample.

Branching by foreign banks is positively correlated with the population, GDP per capita, household disposable income, and economic freedom score of the host country. The opposite holds for the unemployment rate and entry regulations of the host country.

Few paper address cross-border banking in emerging economies. This paper analyzes cross-border branching in Latin America in the context of the current financial integration and bank strategy. Econometrically, its pioneering design allows modeling of inflation of zeros, over-dispersion, and the multilevel data structure. This design allowed testing of a novel country-level variable: the host country’s economic freedom score.